Welcome to Impact Quantum, the podcast where

quantum computing meets real world impact without requiring a

PhD in physics. Today, we've got a mind

expanding conversation lined up with none other than Jordi Rose,

pioneer in quantum computing, former CEO and

CTO of D Wave, and a visionary at the intersection

of AI and quantum tech. Oh, and did we mention

he's literally running across Canada? Just your average

quantum computing guru on a 5,000 mile vision quest.

From quantum supremacy breakthroughs to the future of AGI,

and maybe even the nature of consciousness itself, we're diving

deep. So buckle up. This episode is rated for

Schrodinger's, and it's going to be a wild ride. But first

ten seconds of dubstep.

Hello, and welcome back to Impact Quantum, the podcast where we,

explore the amazing field of quantum computing.

And you don't need to be a physicist, to understand it. We are

here for, as many people as we can, particularly

the quantum curios who are wondering what sorts of

opportunities and career options will be

in a quantum world when we switch from having just

classical computers to kind of the new wave of

quantum computing. Gotta work on that intro a bit, Candace.

Sorry about that. We'll get there. It's okay. We're just happy you've come back to

join us, and we have a great guest today. Awesome. And we're

gonna jump on into all of it. It's really exciting. Yeah.

So tell us about our guest, today, Candice.

Oh, okay. How is the best way to describe, to

describe Jordy Rose? He's a founder. He's CEO of Snowdrop.

He's very excited. He's he's, he's

more technically minded, on the on the

physicist side of how things how things come together in quantum.

And he's about to embark on, several exciting new

projects this year. And so we wanna hear everything

that he's about to embark on. Yeah. Well, welcome to the

show, Jordy. Thanks for having me. No problem. Did

we get the intro right? More or less. More or less. More or less. We're

gonna have to kind of get there. Grab bag of all sorts of weird

stuff that I'm interested in. Your background is very fascinating. I think it's a,

I think it's interesting. One, the running across Canada.

Yeah. I'm fixated on that. It's

like a Terry Fox. I remember as a kid watching the Terry Fox thing or

was that HBO? Like, so what inspired you to because you said in

earlier, you said you're not doing this for charity. Right? You're just doing this as

a personal challenge. That's right. Although I I I

sometimes call it a vision quest. So I used to wrestle and, you know, vision

quest is very important movie for those of us who are in that sport.

And, you know, it was it was it was really the only time that wrestling

was depicted in, like, popular culture back when I was in the

sport. And it had, like, Madonna in it who was at the time one of

the biggest stars in the world. And it was a good movie. That's right. That's

right. This is more like a wrestling in high school too. And for those of

us wondering, like, what do you wrestling is protected in the

media all the time. Different type of wrestling. We're talking Greco and Roman

wrestling, not Hulk Hogan and The Rock and things like that.

Well, my my specific style, the one that we do mostly in Canada is is,

is called free style. It's the it's the one you know, well, there's two that

are competed out of the Olympics, but it's the, it's the one where you can

attack the legs. Yeah. So yeah.

I I wrestled most of my life, when I was

younger. Okay. No. It's it's a great sport. My son,

he went he went from hockey to football to wrestling. And

and when he did wrestling, he really enjoyed it. Now he's at,

University of Ottawa, and he is starting up their first

wrestling club. Yeah. That's terrific. And he just he really loves

it. He thinks it's just such a great sport. And so I'm a

fan. Anything he loves, I'm a fan. So I I grew up I went

to high school in Montreal, and we had a lot of,

competitors and and friends that came from the Ottawa region. In fact, when I was

at McMaster, you know, two of my best friends were grew up in that

region wrestling. So it does have a tradition, of it. But

the university system in Canada is kind of a little bit weak when it comes

to wrestling. There aren't you know, it's not like The US. By the way, just

as an aside, I'm planning to go to the division one wrestling,

tournament in Pittsburgh next week. Oh, very cool.

Yeah. And the it's impossible to get tickets. I mean, unless you're

a a parent or you know somebody on a team, they they sell it immediately.

It's an enormous deal down there. And Canada doesn't have

obviously the same culture when it comes to any sports except hockey, of course,

and maybe lacrosse. Yeah. Curling also.

Curling. Oh, yeah. It's true. My yeah. It does.

But for for wrestling, it's it's, it's not like that

in Canada. So back to the Vision Quest thing. Thing. You know, when it came

out, it was like, hey. That's what I do. And, that's kinda stuck.

No. When I was on the team, that movie was like a constant, like, reference

everything. Like and Yeah. Weren't they running around with their hands like this? I soon

remember somebody doing Vision Quest. I don't remember. Yeah. Well, the

the the the one the one phrase that I always used to use is he

can't hold his own mud. That's right.

It's Matthew Modine. I mean, we're talking Matthew Modine.

Like, you know, my I just remember Madonna. Of course.

Right? Crazy for you. I mean, it was a huge hit. That's right. Yeah. That

was a huge hit. So and I forgot to mention I'm

sorry. I forgot to mention, your you you

being the the CEO and the CTO at D Wave. I

mean, that's gotta be one of your biggest claim to fame.

Your work at D Wave. I mean, everybody's talking about D Wave now. I mean,

we were on a conversation earlier today. Yeah. Right, Frank? And D Wave was

mentioned again. So I'm sorry that I didn't drop that into your

into your intro of of your your bag of tricks.

But, yeah, that's something really exciting to talk about as well,

in the quantum space that I wanna mention after we finish with our wrestling.

Yeah. I mean, especially especially today because the

one of the biggest results in the history of the field,

was published yesterday. I think it was yesterday. It was at least it

was over the last couple days. I was, of course, and so everybody in the

field was aware of it because it was put on the preprint server almost a

year ago. But it's,

it's the only alternate to random

circuit sampling that has a potential candidate for, for

showing quantum supremacy, which is kind of like, you know, the first step in a

long path towards showing that quantum computers can actually be useful.

And and it's a it's a major step because it's kind of like a very

important, hurdle.

And, the there's in quantum

computing is this weird field where no one wants to see anyone

succeed, it seems. So whenever anybody puts up one of

these results, there's an immediate, army of people who try to

show that they're wrong. So that that process is gonna unfold over

the next year or so. But I, I've been staring at that result for

almost a year now, and it's actually right in the middle of my expertise. You

know, it's the sort of thing I studied when I was in grad school. And,

I was pretty convinced that it would stand up once all

of this sort of noise passed. So we'll see. It's not

guaranteed to. But on the other hand, I I do have an instinct that the

sort of thing they're doing is actually going to end up being the

first source of real commercial applications,

not today, but eventually? That's an interesting

question because I think this year started off with well, Willow,

was announced at Google in December. And then

Jensen Huang in the first week of the year at CES kinda was like, well,

you know, maybe it'll be, maybe it'll be five years, ten

years, twenty years. Right? And then a week or two

after the stocks kinda crashed, Bill Gates says, hey, Jensen.

I respect you, but I think it's gonna be sooner to what you think.

But where where do you where do you sit in this? Right? Because you

were, like what do you think?

It's a it's not an easy thing to parse because I think every

single one of those people you mentioned is correct in some way of thinking

about it. The it depends on specifically

what you mean by getting to whatever, you know, step

that you think is important. So I think for for me, the the

most important one of all is

does nature actually support a different kind

of computation from the perspective of

computation, not from physics. We already know that you the physics is

different. That's been known for a long time. But

it's not entirely clear as much as some folks would

like to make you think that the,

quantum physics actually aids computation in

the real world. So actually, can we build machines that that take

advantage of these effects from the computational

perspective? That is a very

subtle question, and it's not yet answered. So what's the distinction

between the two? Obviously, nature is gonna be nature whether or

not we do anything with it. What what is

the shortcoming that Because So I'll get I'll give you I'll give you an

analogy of about how to think about the difference between classical and

quantum mechanics. So in the in the room that you're sat in, there's

a bunch of air molecules flying around in every direction. And

we have the instinct that, there should be no pressure on us. You

know, all of the air is sort of evenly distributed and we don't really even

feel it because pressing on us from all sides. Now, of course, you would feel

it if you went down to the bottom of the Mariana Trench. Like there is

something pressing on you. It's just that we're so used to it, we don't notice

it. So the reason why we

feel that way is that thermodynamics says

it's overwhelmingly likely that all of these things are gonna be

moving essentially in random directions versus each other. So of all of

the potential ways that the air molecules in the room could form,

almost all of them feel the same. And there's only

a few that don't. Like, for example, all the air molecules could for some, you

know, chance of fate all end up in one corner of the room and you're

sitting in a vacuum. That's not forbidden by the laws of physics.

It's just very rare. So the analogy to

quantum physics is that the classical physics, the thing that we're used to, is

like that, thermodynamic thing, the

the the average. Like, the thing that you usually see is like classical physics.

So in some sense, it's a limit of quantum mechanics, but it's not exactly a

limit. It's more like the most likely thing to have happen.

So when we build conventional computers, we build them assuming

that the most likely thing always happens. And,

we engineer them to ensure that that's a fact. You know, it's

very easy to make computers of the scale that they're made

today, like down at the nanometer level, where quantum effects are actually quite

dangerous to their proper functioning. Like, electrons can tunnel out of things and they

can, you know, cause havoc. So a lot of effort has gone

into as you shrink these things, making sure they remain class bits. They're

zeros and ones, and that's all. And they're only zero when you want it to

be zero, and they're only one when you want them to be one and so

on. So the quantum world is,

the is the more fulsome description of reality, which is like the thing where

all the air molecules could be in the corner. So all of those different

possibilities, even the ones that are not likely, you can engineer structures

to try to use them. So imagine there was some magical

thing where I could, I could create a

situation where all the air molecules in the room were in different places or moving

in different directions in exactly the way that I wanted them to. And I could

somehow use that to build a computer. So this is not maybe,

the most easy to wrap your head around analogy, but I think it's actually Or

if I had a wind turbine in my room and by adjusting the like,

maybe I can make it spin. I don't know. Like Yeah. So the the the

quantum thing is is a is is a more false description of reality.

It's supposed to be the way things kind of actually are in some way.

Although there's some question about interpretation of it. Like, what does it actually mean?

But the actual, like, mathematical physics of it,

regardless of how you interpret the equations,

allows you to manipulate the state of the world in ways that

you can't with classical computers. So when it comes to the computation

side, you can imagine it as an expanded set of possibilities.

So I can do things to the the information in the computer that I couldn't

otherwise if I was just using a classical computer.

And on pencil and paper, there are there are algorithms,

processes for using these things, which are appear to be

more efficient, which means they take a lot less steps. And the,

probably the best that you could do is exponentially less steps, which is a

big difference. Now the the reason why I'm

hesitant to claim victory on this is that this has never actually

been demonstrated. So there's a there's a lot of times

when our best theories of nature make predictions

that turn out to be wrong and they unzip the

theory. So there are what that means is that there is a different

theory that might supersede them in the conditions in which you're building the

machine. And I think that there's not an unlikely possibility that when we

build large quantum mechanical systems, they don't work the way we think they

do. And, quantum computers will be a test bed

for this. So there's, there's an ongoing debate

in the scientific community where 99.9%

of physicists are on the side of, yes, of course, quantum computers will

work. But there's a very small number of folks on the other side

which are like, no. I have a good reason for why they might not. And,

the the media and all of this isn't aware of the subtleties of these

arguments because it's always like big step towards billion

whatever, which is not the right kind of

description of where any of this is at. This is still a

situation where there are basic physics

science questions that still remain to be answered. And

the D Wave result is an example of pushing science

beyond where it was before. So they they've answered a question, I think,

that, was a very important one. It says, will the approach that they're

taking scale to the low thousands

of qubits? And it does, which is not was not

guaranteed. It could have all failed, but it didn't.

Interesting. So is this is part of this why error correction has been such

a barrier to this point where the systems may not behave the

way we think they will? Yeah.

So there's there's what usually people talk about

quantum error correction, they're talking about error correcting a very specific model of

computation, which is called the gate model or the circuit model. There

are more than one ways to to build a quantum computer. And that

particular whole ecosystem of ideas applies only to one of

them. So this is another subtlety that is important to understand is that not all

quantum computers are the same in terms of the operating principle.

So this is a photonics, ion traps.

No. That's that's that's the hardware platform. So this is a this is a

level too. This is, like, a meta thing. So for example, I could build

a computer using, like, a physical neural net if I wanted to. We have one

in our head. It's called a brain. The brain doesn't operate using the same

fundamental principles as digital computers. Like, we

don't exactly know how the brain works, but it's pretty clearly the case that it

doesn't have gates and it doesn't have, you know, memory registers of the sort that

you find in a regular computer. It's architected differently. It has a different

operating principle. So when you build a computer, you're not

bound to use the same operating principle that conventional

silicon computers use. That's what the gate model is.

But you can you can try to do different things. So the gate model, one

of its its advocates point to this idea of error correction as

being one of its strongest features. So in theory, anyway,

you can build, redundancy into the

computer of a sort that's not exactly the same as classical error

correction, but close, where you measure some subset

of the information that you're trying to process. And based on that,

you conditionally do things that are supposed to regenerate the

full quantum information. So again, on paper, in theory, this

works perfectly fine. In practice, the willow thing

and some of its cousins are attempting to show that it

actually works in practice. And there's some very promising results, but I

still say that the jury's out. No one's ever built a fully error

corrected, computer. There's attempts to

build fully error corrected qubits, which are progressing quite nicely,

but there's a long way between building an error corrected qubit and an error

corrected computer. Those are very different things. Oh, I

see. Well, that's so interesting. I I did I hadn't realized that.

And when I thought that error correction was a a

common a common barrier, and here you're saying no.

It can be done a different way. There's there's yeah. So there's a

couple of things about this. So one of them is that the there are different

ways to get at errors. One of them is you reduce the source of

errors. So that's an obvious thing. Right?

And there's a long way to go before the current

quantum computers get to being mobile to reduce the

actual errors. Because in conventional silicon, most of the

errors come from rare events like, you know, high energy gamma rays

hitting a chip, which flips a bunch of bits. Space is really a problem

for satellites and anything in space. Well, it's more of a problem. On the

Earth. Is that a More of a problem when you don't have something in the

way, like an atmosphere or an ocean or something. But it it's,

it's always a problem all the time. You know, we're the there are always these,

like, high energy bullets firing at us from all over the place. And so they're

they're there. In the quantum

world, the fabrication technologies, the things that are

actually make the chips themselves, are not nearly at the

state that the silicon guys are at. And what that means is that they introduce

a lot of defects because the processes aren't as well studied. So if I

put a little bit of oxide where it shouldn't be, I've got this massive source

of noise. And so the, the, a lot of the work that's been going

into quantum computing is actually in the material science of making the

processes themselves such that the materials are ultra

pure. There's no noise sources that shouldn't be there so that the base

level of noise keeps dropping and you get more out of that than out of

quantum error correction by orders of magnitude. So, like, when I was at D

Wave, nearly all of the money we spent was on making

fab better, like, making the fabrication process better and better and better. And it

continued after I left. It's still the most important thing for reducing noise.

So the D Wave process, the the the computational process they use,

there's a natural error protection mechanism that's baked into the

way that the model works, which was done on

purpose. So we chose that model because it has natural robustness against

noise. And then the idea was crush the noise as low as you can make

it and cross your fingers and hope that you can make it low

enough so that the natural robustness against the noise, is

good enough. And it turned out that that was a good bet. It is. So

the the natural robustness against noise is enough now to

protect against the natural sources of noise without doing any

error correction at all. And, that's part of the

evidence that was shown in this March preprint that got published in Science

yesterday. Interesting. Okay.

Okay. So I have a lot of questions.

I probably have to have you back. Is this too technical, by the way?

No. I I like it. And, you know, what what we've done actually for the

show is we we we we rate shows something like zero from zero to five

Schrodinger's. Right? Okay. So, like, it's kinda like I know. Right? Like,

level of difficulty. Like, I think We're definitely at four Schrodinger's right now. Alright. Well,

I was gonna say, but but you don't hold back on the Schrodinger's. No. But

I'm holding on. See, the issue is if I can hold on, then we know

we're okay because I'm the quantum carrier. Canary. She's our quantum

canary. I am the quantum canary, if you will. And I am absolutely

holding on. Because I think that people have to understand this

particularly, like, particularly if you're a wannabe investor.

Right? You have to understand that. And I didn't know this because it's not I've

been playing around with this off and on getting into this space since

2019. Right? So I didn't know that the fundamental,

like, understanding of this was not a done deal. Right?

And I understand there's a lot more complexity to

this than, you know, traditional electronics, but, I

didn't know that it was very much in doubt up until, you know,

read this recently. I thought it

was a foregone conclusion that this was figured out on a chalkboard or a

whiteboard many years ago. But then again, as I

say that out loud and I think it through, like, well, a lot of things

work well on a whiteboard. They don't translate into reality.

Yeah. I'm sure that they had the analog of the chalk slate when the they

thought that the Earth was the center of the universe, and they could draw pictures

of that too. But it turned out not to be true. That's true. A lot

of this a lot of this stuff could end up in that kind of category.

That's that is true. That's a good way to put it.

There's a lot we can kinda go into. And I think one of the things

that really interests me is you're one of the few people well,

one, I have a lot of questions about D Wave, but, I will ask

that one right now. What exactly is quantum annealing? And it's my

understanding that D Wave is kinda that is their

center of gravity. What is annealing exactly?

Is it it's it's really good for finding loss. Is that

do I have that correct? So let's,

this is a couple of ways I can answer this, but let me try to

do, like, a little bit of a historical thing. Okay. So back

back in the beginnings of iron working and eve maybe even

earlier, people notice that if you heat it up metal, like

an iron sword or a plow or something like that, and then you cooled

it, by immersing it in water or

oil, the properties of the metal changed. So they

would go from being, say, soft to hard or

or or brittle to, to not.

And that, that thing is

called thermal annealing. And if you if you if you look up,

annealing on Google and you and you watch, what you'll find is a lot of

videos of people taking very hot metal things and dunking them

usually usually in oil, because it

changes the properties of the metal. Okay.

So, about a hundred years ago or so,

there was an idea that you could model what was happening

in these metals using statistical mechanics. So there's a bunch

of things in the metal like atoms or something,

and they would point in different directions. And

if you heated them all up, they would start pointing in all different directions and

sort of shake around because there's so much heat in them like see, think of

like a metal glowing white hot. All of the things inside it is almost a

liquid. You know, they're all moving around and all free to move. And then

when you cool it, what ends up happening is they can't move around as much

and they get locked together. So if you

so this was like a theoretical thing about a hundred years ago and then in

about forty years ago, some smart guys said, hey, we

could simulate this on a computer and we're gonna call it simulated annealing.

And And what we're gonna do is we're gonna have a fake thing called temperature

that makes things move around a lot. So the higher that number is, the more

they move. And then what we're gonna do is in the computer, we're gonna lower

that number slowly and we're gonna watch what happens to the things.

And what you find is that if you do it fast, you get one

answer. You do it slow, you get a different answer. And then the

the light bulb went off and connected it to a whole bunch of other problems

which have to do with optimization. So optimization is finding

the biggest, the smallest, the lowest, the highest. And it

that algorithm of heating things up and then cooling them down

was a new way to try to find the lowest

point on a landscape, say, which is an optimization problem. And one of the

to sort of see the analogy, imagine imagine that

the high temperature thing is like exploring all the possibilities,

like all of the different things that could happen or kind of like zipping around.

And then as you cool it, they have to choose one

configuration. And the kind of like a ball rolling

down a hill. So if I've got a ball at the top of the hill

and I let it go, eventually, it has to settle down and choose where it

wants to be at the bottom of the hill. So this annealing thing is kind

of like that. And it became a ubiquitous way to

solve hard problems of a whole bunch of different kinds of sorts.

So quantum annealing is like that except the thing that you're annealing

isn't temperature. It's the amount of superposition

in each qubit. So imagine you've got a qubit and think of it

as an arrow. So there's an arrow pointing up is digital zero and

arrow pointing down is digital one. And often in my

world, we call these things spins because the analogy is to

like a little top that's sort of spinning counterclockwise or clockwise.

So up is zero, down is one. So at the beginning, what you

do is you take all of your qubits and you place them in an equal

superposition of these two states, which means that in if you

think of them as little magnets, you apply a field that's

transverse to that direction that there's pointing it. So the magnets

start pointing this way. So they're not up or down. They're

in a superposition of the two. The probability of measuring each is fiftyfifty

to all of the qubits in the processor. So this in a magnet is

called a paramagnet. It's a state that doesn't have any preferred direction. It's

the analogy of a high temperature state in if you were using temperature. So

there's no decided direction for any of the qubits.

Then what you do is you slowly remove this tunneling term, the term

that allows the superposition, in the background of another

term, which is the problem you're trying to solve, which encodes the

landscape. So this you wanna find the minimum of a landscape.

So what happens is as that it this term turns off,

the bits have to choose which of the two states they're going to be

in. And then at the end of this process,

you measure the states of all of the bits and you get a bunch of

zeros and ones, which are the directions that they're pointing in, which if

you've done a job right, is a is a low energy sample from the

probabilities of of being in each of these states that

preferentially favors the lowest energy solutions. So if I if

I was to say, you know, I wanna find,

let's say, the,

the let's give an example of an optimization problem. So let's say I'm an engineer

and I wanna build a bridge. And I've got 10 different

parameters that I'm trying to trade off, and I have to I have to do

it with a certain budget and certain safety parameters and

certain etcetera. So I could go down the list. So what I wanna find is

the cheapest build that satisfies the safety

parameters. So when I run the system, I encode that problem in this

thing that, you know, it's trying to optimize. I throw the switch, the d wave

system anneals in this

quantum annealing way. And then I get the answer. And then what the answer

is is the setting of all of those parameters that is supposed to,

satisfy my constraints best they can find.

So it's directly analogous to thermal annealing. And,

but the process that it's using, the physics it's using is very different.

It's now the annealing in, in quantumness,

if you if you wanna, like, look at it that way. So if you wanted

to find the global minimum, this is ideal for that.

Well, not necessarily because the system some problems

finding the global minimum is hard even for quantum computers. Mhmm. And

so the what you get is a sample from the low energy solutions.

So what that means is that let's say there was a hundred million ways to

build a bridge and only a thousand of them fit

my description, but one of those thousand is the

best. I'm not guaranteed to get that one, but I'm almost certainly

going to get one of the one thousands. So if I don't care about getting

the best solution, but I just want a very good solution very fast, these

systems absolutely shine. And very fast means very fast. I can

sweep this thing now about a nanosecond to get an answer.

So in just just to set up one of these competing

simulated annealing or tensor networks or whatever ways can take, like,

hours sometimes. So this thing, you just send up the send it

to the problem. You get back the answer in, like, less fraction of a second.

Wow. Yeah. Wow. So I've been using them now

for almost a year for my own personal work, and they're super robust.

I mean, one of the other things that isn't talked enough about is that all

these other quantum stuff that people use is very flaky.

The D Wave stuff is just rock solid. It just always works.

And they've been in the game a while. Yeah. I founded the

company in 1999, before anybody thought it was a good idea to

do quantum computing because it wasn't even sure that you could build even a qubit

back then. But yeah. So it's been, what, twenty five

years? Wow. Wow. And

are you and are you still affiliated with D Wave or no?

No. I I left, my position in

2014 to to, to go into my second career,

which was in AI. And, well, it's what we

would call AGI these days. It's general intelligence for moving

robots. Interesting. Yeah. And and so so what are you what

did you what are you working on now? Because you're really as I

understand it, kind of in that that intersection of AI and

quantum computing. Yeah. I think my, my my

fundamental love is is reinforcement learning. So this is the area of,

AI that I think is the most likely, model for,

living organisms. So if we're gonna build, like, computational models

of life, it's the obvious number one

choice. And, if I find it fascinating

that such a simple paradigm could potentially describe,

you know, most of the types of things that, you know, we

take as granted or being around us agents. Things that make

decisions. And it touches on a lot of deep philosophical

questions about free will and consciousness

and, what it what the words that we use

to describe ourselves actually mean technically. Like, what does it mean to be

intelligent? What is a life well lived? All

of those sorts of things can potentially be

approached from a technological view.

So I find that fascinating. Much more fascinating than quantum computing. I think

quantum computing is more like turning a crank. Like, we already know the rules of

quantum mechanics and we already know how to build things. It's just a matter of

time before we combine the two. But agency

is a different matter. It feels to me like it's

not, a turning the crank kind of

thing. It's more like, a real exploration.

Whereas the quantum computing thing feels very much to me like an engineering

project at this point, which doesn't mean that it's not worth doing and it's

not great and terrific and all that. But, it's not the sort of thing

I'm interested in. I think I'm more interested in the kind of

frontier things. Yeah. That's I mean,

reinforcement learning is a fascinating field, and you can

build very complicated I wouldn't call them agents,

but if but you can build

really advanced outcomes with relatively

simple code. Right? And I'm thinking of the multi

armed bandit problem, which is basically the idea of simulating

slot machines. And you can

maximize how greedy you are. If based on a couple of, like, just

small parameter tweaks, you can change your entire

outcome. Like, basically, I it's just fascinating. And this this kind of I

don't wanna call it intelligence, but some kind of something emerges

from kind of the randomness, which I think is very fascinating.

Well, the the thing I like about the the the reinforcement learning thing has always

turned me on because it's it's got a combination of things that are very,

difficult to find in a frontier area. One is that the story,

the fundamental picture of reinforcement learning

fits in one diagram. There's a very simple diagram that

is like and I think it's figure 2.1 in Rich Sutton's book,

which has, you know, three boxes and five arrows, and

that's it. So it's such a a simple idea,

but it when you start unwrapping it, it leads

to a universe of complexity and and and it

encompasses virtually everything that philosophical

folks have ever thought about. You know, it it has something to say

about virtually every question that people have ever asked themselves about, you know,

their nature of the themselves in relation to the universe and so on.

It's very much it it strikes me that it's very much like,

so Einstein's equations or the Schrodinger

equation are the symbols that you can write down on

the palm of your hand. You know, they're just a bunch of strokes of a

pen and you look at it and and that thing is supposed to

encompass virtually everything there is.

This diagram that describes reinforcement learning to me is like

that. It's it's like a fundamental equation

that but it's not an equation. It's a picture that,

is has within it. It has multitudes within it.

It traps within it the, an enormity

of, of different roads that you can

travel through it to try to answer all of these questions. And I

really don't like the type of

exploration that sometimes people do where they try to answer

deep philosophical questions about, you know, the meaning of life and free will and all

this with words. Because nobody agrees on what any of these words

means and ultimately it's just a bunch of hot air. I think if

we're going to try to really come to terms with

the the truth of, you know, what we are

and all of these things that we think about ourselves, we need

to do it in a way that is

computational ultimately. And what I mean by that is we have to build

things that exhibit the properties that we think we are

trying to understand, like intelligence, consciousness, free will, and so

on. If we can't build a machine

that has a thing called free will, it doesn't

exist. Like, that's my position. Or

we haven't asked the right questions in order to get to the point of actually

asking a question. A bunch of philosophers debating the point about whether there's free

will. You might as well have a bunch of, you know, gerbils running around in

a cage and and get the same kind of quality answer up because it

doesn't mean anything. Like, the only thing that means something is whether you can

build it. And and again, in my view. Well, it's like you said earlier, like,

you know, like, on a chalkboard, you can probably make anything work. Right? Hey.

The Earth is the center of the universe. Right? Yeah. But even on the chalkboard,

there's different degrees. Like, I could say, I'm gonna write down Pythagoras'

theorem, and I'm gonna prove it given these axioms. So I could do that on

a chalkboard. I'm not talking about real triangles. I'm just talking about like abstract triangles.

And I will believe you because you've you've laid out your axioms. You've used

sensible proof methods using logic, and you've gotten to a conclusion.

Most of the discussion about the properties of the human mind are nowhere near

that. There are a bunch of people who've usually taken too many

psychedelic drugs getting together and in a sauna

and, and jawing at each other. And sometimes these people have

respectable titles and call themselves philosophers. But for my money,

none of it means anything. I think the only way that you can make progress

on understanding these things is to actually go in and understand

them from the perspective of, you know, science and technology in a way that

you can actually build something that exhibits those

properties. And so right now, my my desire

is to deep dive into the whole reinforcement learning paradigm

and see if there are ways that I can come up with

to, to start to use those tools and

the kinds of things that people have done in that in that field, which

are monumental achievements, in order to try

to, pry the lid off some of these questions. And it's

not the sort of thing that you do in a company because it's not really

a commercial endeavor. It's more like a, scientific thing.

And because I've I've been lucky enough to be able to fund my own

research, so to speak, I don't need to do it within some hidebound

old dusty university. I can do it by myself.

So so do you this comes up a lot in

AI circles as I'm sure you're aware is like the whole idea of artificial general

intelligence, right, and consciousness. When would we know a machine

is conscious? Right? And I kinda mentally struggle

this because I feel like in order for

us to say yes or no to that

question, we have to have some kind of

mathematical definition of consciousness. A

verbal definition of consciousness, I humanity has it figured out

in six, seven thousand years of recorded history.

I don't do you think we can get to a mathematical definition of it?

Well, I think if you're going to talk about whether a

thing has a property, you

can wave your hands and kind of

approximate an answer, which is typically what

we do. Like in in not only in things like consciousness,

but everything. Like if I if I ask you, does the thing have a property

you look at and you say yes or no? It's not usually some kind of

mathematical thing. It's more like my intuition about whether it's there or

not. Like if I if you give me an orange and you ask me, is

this an orange? And I say, yes. I haven't proved anything mathematically. I

just think it's an orange because it looks like an orange. And I think things

like consciousness, we tend to apply the same protocol. Is that

if something looks like it's conscious, we say it is.

That's that's satisfactory if you're an agent kind

of exploring its environment and doing your normal things. But, it's not

satisfactory if you have to build it. Which is why I keep coming back to

this thing that if you really wanna understand something,

you have to be able to construct it in a

machine. And so the question about consciousness

for me, it's not an interesting question to ask, say,

is a rock conscious or is a photon conscious because it doesn't mean

anything. It's like saying it's it's just a bunch of words that are strung

together that have no semantic meaning. What you have to do is

first define what you mean by that word. Then you have to

show that that you can build things that have or don't have it or have

it in some degree. Then, you're somewhere. Because now, I've

said this is a thing. You can disagree with me if you like, but this

is my definition of what this thing is. I'm gonna build a thing that doesn't

have it and then I'm gonna build a thing that does have it and then

we're gonna look at them and you're gonna tell me what you think about these

two things. So, in the case of a

conscious experience, which is a peculiar one

because people often claim that there's no way to make

progress on this because of the so called hard problem, which by the way I

refute, I don't think there is a hard problem. There is no magic in this.

This is a, an illusion. And this is

probably if if you if people wanna kinda see a strong defense of

this perspective, read or watch Dan Dennett. So

he's the clearest thinker about consciousness that I'm aware of.

And, he's remarkably deep

in a way that you might miss when you first read it

or see it. So you have to sit with it for a while and really

understand what he's saying. But I think he's got he's got the answer somewhere in

there. So when I when I think about what it means to build a

conscious machine, I have a I have a prescription. So the

first thing is the machine needs to be embodied. That means it needs to have

a body in the world. It needs to be able to develop a model of

itself and the world around it where the model of itself

is distinct from the outside world. So you

in your head have an idea of you which is not the same as

your desk or your your plants or whatever. So this system has to

have what's called an inner world model that's sophisticated

enough to be able to model agency of both itself and

others. That process begins

imbuing the embodied agent with what we call

consciousness. And that amount of consciousness

is related to the quality of the model. So as your

model gets closer and closer to being able to model the actual real

world precisely, you become more conscious in my

view. So this, totally mechanistic

view of consciousness is something that can be tested by

building machines that have these properties and ones that don't and seeing

how they behave. So I think what will happen is that you'll see

differences in behavior between these two. And having an inner world model allows

you to be a better agent because I can predict what's gonna happen better because

of the model of the world in my head. So I can ask what if

questions about the world. If I if I pick this thing up and throw it,

what's gonna happen? If I, you know, go up behind this person and I light

their hair on fire, what's likely to happen? So questions like that to us

seem stupid because obviously, you know, that's not great. But you require

a model of another agent that's like you in your head because what you're thinking

Is that like theory of mind? Is that what people Yeah. Well, it is. Yeah.

So the reason why you you think it's absurd to light someone's hair on

fire is because you imagine it happening to yourself. So this

property that we take for granted about the way we think about the world is

a necessary component of consciousness. So in this model, things like

photons and rocks and even most animals are not

conscious because they don't have inner world models. They arise from probably from the

cortex. So machine animals that don't have cortexes

are likely not able to sustain conscious experience of the

sort that we have. So I guess where I'm where I'm all going with this

is that the original question you asked is what am I working on? So it's

stuff like this. It's the, the intersection of reinforcement

learning with kind of deep questions about things like this, with quantum computing

thrown in the mix wherever it fits. So sometimes you can put

quantum computers into this picture and get something interesting coming out.

But, you know, I'm only doing that because I know I know how to do

it, and it's kinda low hanging fruit. Alright.

No. I mean, I I I personally could go down this rabbit hole a

lot longer, because it always

fascinated me where

science and philosophy and math kinda all converge,

and it's not a clear line which is which.

Right? And I went to a Jesuit high school and Jesuit university, so

maybe I'm a little more predisposed to that than than the average

person that get lost in philosophy. But I think it's an interesting question. I

think the practical question is, like you said, like,

you know, I can't imagine all the ethical and public implications

that would come about if we did determine if we did have

some kind of mechanize or or or idea the mechanics behind

this. And I also wonder too, like,

maybe because of our theory of mind, we tend to anthropomorphize things,

whether it's, you know, a

ship. Right? What sailors always call their ship, chi. Right? Like, it's it

becomes a thing. It kind of and it's probably

not conscious. Like I really can't say. Right? It's I think, therefore

I am. Right? So it's I don't know. I've I've always been on the thinking

that, like, consciousness is is a subjective experience.

Well, we definitely do use this machinery if I'm right about the way

this works. The the the idea that there is

another agent that's like me, that naturally means that

anything that moves in the world, including ships. Right.

Is potentially an agent. And we are going to imbue it with the kinds of

properties we generally, associate with ourselves. It it

is an important thing that movement thing is super important. Is that we tend to

think that things that move around are like us and things that don't aren't. So

if you think about like a tree, you think that's not as much like you

as an ant. This is a natural side effect of the,

the way that our minds evolved is that things that move are different

than things that don't. And by movement, I mean, locomotion, like

actually going from place to place. So things like ships and cars

and bikes are, more natural to

anthropomorphize because they move around and they're more like animals

than, you know, something like, I don't know, a tree.

Well, and the tree is not a threat, like, evolutionarily. Right? Like, you know,

tree is not a threat unless it's falling down at you, which which means it's

moving. And it's even though it may not be moving of its own accord,

Right? It's moving in or yeah. Moving things have the potential to be

dangerous or free. Yeah. No. I mean, that's fair.

Wow. This is I love it when we go deep philosophically. I think this is

the first time we did it. Candace is is holding on. She's doing well.

She's doing well. She you're on mute.

She's still on mute. While she figures that out.

So what I love in the philosophical conversation.

Yes. Why in Columbia? She went to Columbia, so she she's good. I went to

Columbia. I did the core. I know how it goes. You know what I

mean? But, but I think it's really important. And I think that,

again, you know, bridging this into the real world, talking,

you know, talking about how do we relate to a tree versus an ant and

the consciousness and subjectivity. I love this stuff.

I love this stuff. Well, this isn't just philosophy. Right? Because what I'm

saying is I wanna be able to build things that have these properties.

And the this is something that is an

important thing is that if you can build things that

have first person perspective and are what we would

call conscious Scentsy. Right?

Well, again, it's a it's a definitional thing, but maybe.

Those sorts of things we tend to again, because we

associate us with being the center of the universe is anything that's like us gets

more rights than things that aren't. So we'll naturally want to be

able to ascribe rights to these things

and, that'll be a different kind of thing because we haven't had to deal

with that before. And I think one of the reasons why we're going to have

to, whereas we don't with say the other great apes and other things that are

obviously like very, very close to us in terms of their mental,

you know condition. Is

is power is that the sorts of things that we're gonna be building

will be better than us at nearly everything. And so the the

reason why we will ascribe them rights is that we'll we will have to because

we won't have any choice. Because we're gonna have to we're gonna have to regulate

it and control it. Well, you're never gonna be able to regulate or control it.

I was gonna say control is gonna become an illusion. Yeah. So yes.

But Rich Sutton does a great job at explaining what

the future is going to look like here. And the we have to let go

of the ideas of control and regulation because shortly, we're not going to

be in a position to be able to impose either.

And that's not a bad thing. You know, I think a lot of people are

terrified of a world where, you know, you're

not the top of the, you know, the ecosystem

or whatever, but we're already not. I mean, people have the illusion about

the position that humanity has on the planet. Like there are way more

bacteria than us and there always have been and there always will be.

The, the, the, the emergence of this new kind of

thing, I think is, is something that we need to prepare for, but not with

hysterics. We need to prepare for it with

a way of thinking about, you know, our place in

the universe that's a lot more humble. So we typically view that we're,

like, in charge of everything and everything goes exactly the way we say it does

because, obviously, we're the lords of the the kingdom. But that's a

very provincial way of looking at things. You know, there's like hundreds of trillions

of habitable planets in the world, in the universe, and this is

probably filled with life. And, we're just

a tiny speck in the middle of the back end of a

tiny little place that most of these other civilizations will

never even know about. So I think that kind of like being

a little bit more humble about our place in the world and seeing the opportunity

to understand, who we are at this level as being a great

gift is the right way to start thinking about the

future that we're about to, to enter. That's a

good way to put it, you know, because I think people would be shocked to

learn that there's probably more bacteria in us than there is us.

Yeah. By a lot. Yeah. And, like, not even close. Right? Like, this so,

like, then what what is us? Like, what is us as an individual? See,

that's the thing. Right? And I think like the whole reinforcement learning paradigm is

kind of a tool that you can use to try to understand what does it

mean to be you? What is yourself? What is that thing you think of when

it's you? Because you're right. Like our actual physical bodies

are filled with things that don't have our DNA. They're bacteria that kind of,

like, hijack our, you know, embodiment. So what is it? What

is you? Like, how much of you could you remove before you wouldn't be

you anymore? If I cut off my finger, am I still me? Like, what does

that mean? So I think that this sort of thing,

when we use words to talk about it and we have, like, philosophical

discussions leads nowhere. It's a giant circular washing machine of

doom. You know, it doesn't it doesn't end it doesn't doesn't

end in anything that is useful. And here here I'm

thinking I need to go take myself a good nice silk wood shower.

No. So I think like the only way bacteria. The

only way to do this is to start building things that either do or don't

have the properties that we define, and they have to be real things that we

can measure. If you can't measure it, it doesn't exist as far as I'm concerned.

And that makes a lot of sense. We got way off quantum computing,

but no. No. Like, it's I think it's important. Right? Like, it's, like, there's

plenty of philosophy majors out there that are gonna ponder, like, what am I gonna

do with my career? Right? Well, I think you're I love you all.

But No. No. You're you're you're more useful now. I think actually philosophy is

gonna be a very important thing because when you do

this thing that I'm talking about, all of the tools of philosophy become

real things that you actually have to use in engineering. Like, it's more

important to have philosophers around because they're used to thinking about things in

a certain way, very precise definitions, making sure you don't

make any fallacies and so on. Like, all of that stuff is just like

hot air until it's connected to the real world. And now we're using

technology to explore, you know, problems that have been with

us since the dawn of thinking. And, now we we're at the

position where we can actually make progress. So the all the

philosophy folks are a way more important now than they ever have been.

And they need and, you know, if I was a a young person, I would

absolutely make sure to include the kind of

the curriculum that people go through when they learn

about how to think. That's super important. Critical thinking, it's it's killer. The

critical thinking, the linguistics behind how to

how to put together your thoughts. Even

psychologists now have a major place

in business because their businesses are trying to work

out all of this, like, personality testing. And if, you know, if if a person

does this, they wanna understand how people think, and how they're gonna

react. So these are actually very important professions,

that are going to touch upon more, you know,

scientifically IT minded professions in the future. They're

gonna need the psychologists, the psychiatrists,

the great critical thinkers. Well, even today, you can see, like,

people who are really good at language arts, whether those be English

majors, whether they be lawyers, are going to have a

much better, I think, time with

prompt engineering Mhmm. Than the average Joe or Jane.

Mhmm. So all of these things that I think it's interesting if you kinda

think about education along with you. Right?

Like, you know, first it was get a trade.

Right? And then it was get a college education,

then it became get a college education in STEM.

Now people are realizing, well, maybe we need to have the trades. Maybe

the philosophy stuff that we thought was, quote, unquote, useless.

And I'm quoting my parents there. When I was when

I was going to school, I was like, he had some interest my dad had

some choice words about you gotta get a real degree.

And, and and what's real and what's valuable is also

very subjective. Right? I mean, I had to convince them that computer science was a

viable course of study. Right? I mean, I

had four choices as a kid. Like, you know,

doctor, lawyer, engineer, or, you know,

sign up for the military and get a trade that way. Right?

And convincing them that computer science was a

viable math didn't make cut

because, you know, it wasn't strictly speaking engineering, but, you

know, software engineering as a term hadn't really come about yet. So

convincing them that computer science was actually a viable career

path involved me actually getting a printed copy of the New York

Times job section on Sunday and showing my

dad the pages and pages of stuff and my mom too.

I I think I think you're right, though. Like, what

what is quote unquote useful to society?

Money is obviously, I think, a good proxy way to measure it.

I mean, sad but true. Or

it changes over time. Right?

You know, if there's an apocalypse and all the computers go away,

right, then the ability to hunt and, you know, fish

and grow food then become the desirable skills.

Yeah. And I I'm I think that the money is the way

we measure value. Like, that's the way the world

works is that we we we trade money for things we need, like food and

shelter and so on. I mean, the, it's the best

system that anyone has ever thought of for building a society

that works, where we can specialize and do different

things. Yeah. And what what becomes important in

societies over time, obviously, does change mostly because of technology,

but also because of culture and so on. And

I I'm I'm often asked, you know, what what would I

recommend people do, you know, in school for their kids and

things, facing this new world? And I don't

think that my answer has ever changed. It's just just do what do what

you love. Like, I think that there's an an

an assumption that there's like a

coal mine mentality where you have to work in the coal mine because that's the

only work there is, but you don't like the coal mine, but you're going to

do it anyway. I don't think that's the right way to think about

living your life. You know, I've never had a real job.

I've always kind of created my own jobs about the, you know,

around the things that I wanted to do. You know, like first it was quantum

computing and then it was reinforcement learning for robots and then it was humanoids.

None of those things existed when I started. You know, each of them was a

new thing that didn't have even names. We can call them these things now, but

back when we started each of them, they didn't exist. So I

think that there's an undervalued aspect of

education, which is to learn about things that you care about and don't

care about whether they're useful or not. Because I think that the more

you love doing something, the more likely you'll be good at it. And when you're

good at something, you attract good things into your orbit. It doesn't matter what it

is. If you're a good painter, a good musician, good at writing, good at playing

video games, good at whatever. You know, the goodness

attracts other people who are also good at whatever you're doing. And then you

build, you know, a community and then something will happen that's

good. Okay. I think that the the worst thing you can do is, like, you

know, go into something because you think it's going to be a good job. I

mean, what a soul defeating thing that is.

So with young people, I always tell them, you know, find out what you

love doing. This is gonna be a process because you don't know yet. But once

you do, then do that and don't worry about the money thing. It'll it'll

come. That's a that's a that's a

very inspiring way to look at it. I like that. And I think

that that's a great way to wrap wrap up, you know, what we're

talking about. I think that you have a phenomenal

perspective, on the quantum ecosystem,

on what's important, on what's going on, and where it needs to

go. We most definitely are

gonna have you back. Absolutely. Because you

really like, I'm I'm eating it up, and there's just so much more that you

have to talk about that I think is vitally important. There's a whole

hundred other questions I couldn't I we didn't get to, but I think this is

good. This is good because I think there's a lot of people out there that

are struggling to figure out what does what does life look this is probably

I'm pretty sure several generations ago when people went from

agrarian to industrial, there was a lot

of confusion and chaos too. But I think that

this is something that hasn't been around probably in living

memory. So but I think it's I think it's a

valid conversation, and quantum is gonna play a role in it. Will it

be the role? I don't know. I can't predict the

future. I always tell my kids if I

could read minds or predict the future, I would never leave Las

Vegas. They probably kicked me

out first, but, but then again, I guess I'd see it coming. But,

the good. Somebody laughed at that. I'm good. But we definitely wanna be respectful of

your time and our listeners' time too. But this has been an incredible time. And

if you're willing to come back, we'd love to have you back. And, safe

travels on your trek across Canada. Yeah. How how long are you gonna be

running for? Is it a distance that you're trying to hit? Or is it,

like, you hit a wall and you're done? No. It's a distance, and

it's probably gonna take about a year. It's about

8,000 kilometers, like, 5,000 miles,

from Tofino to Cape Spear. So it's right across the

entire, entirety of Canada. And only a handful of

people have done it before. So it's, it's a it's a it's a

monumental challenge, mostly a fight against the weather

and, the, the grind, you know,

because it's every day is fairly easy, but you stack

300 plus of them in a row and it becomes difficult.

And you're not and you're not doing any kind of fundraising for anything

anything along the way? I mean, it kinda seems like it's a wonderful opportunity.

Yeah. I I thought about it, but I I this is more about this is

personal thing for me. Not I don't wanna speak to public.

Cool. Fair enough. Feel feel free to wear your,

Canada's not for sale T shirts

or your elbows up. You know? I've I've now had to

purchase multiple for my husband and my son, so feel free to wear the proper

the proper accoutrements as you're as you're running. But I

think that's fantastic. Absolutely. So we're gonna be bothering you along your

way, to have another conversation because I really Frank, I

have so many questions that we could continue on. He he's brilliant,

and it's very exciting what how he's explaining it. That's

what the curious are gonna be so excited about, how you explain

it and make it approachable for everybody. So that's wonderful.

Excellent. Well, with that, we'll let our AI, who may or may not be

sentient or conscious, finish the show. And that's a wrap for

this episode of Impact Quantum. Huge thanks to Geordie

Rose for blowing our minds not just about quantum computing,

but about AI, consciousness, and, well, the entire

nature of reality. If your brain is still intact,

be sure to subscribe so you don't miss the next deep dive into the

quantum realm. Got questions? Hit us up on

social media or visit impactquantum.com to continue the

conversation. Until next time, stay curious, stay

quantum, and maybe start training for your own vision quest.